DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is sent in response to Applicant's Communication received on August 18, 2025 for application number 19/3022,308. This Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawings, Abstract, Oath/Declaration, and Claims.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/26/2025 is noted. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 8-10, and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Ash (US 2023/0385300) (hereinafter Ash) in view of Mudigonda et al. (US 2023/0074414) (hereinafter Mudigonda).
Regarding claim 1, Ash teaches a system comprising: at least one hardware processor; a non-transitory computer-readable medium storing instructions that, when executed by the at least one hardware processor (see Fig. 4, discloses memory and processor), cause the at least one hardware processor to perform operations comprising: receiving, via a graphical user interface, a definition of a transformation flow between source data and target data (see Figs. 1-2, Table 1, para [0044-0045], discloses Treasure Data platform receiving pipeline instruction between source and target data, it is known to one of ordinary skill in the art that Treasure Data features a browser based graphical user interface): generating a virtual procedure corresponding to the definition of the transformation flow (see Figs. 1-2, para [0044], discloses generating data pipeline instructions according to programmed pipeline of steps), storing the virtual procedure in an in-memory cloud database (see Figs. 1-2, para [0039], para [0044], discloses storing data pipeline instructions in target database system).
Ash does not explicitly teach the source data and the target data being data from a data lake that is stored in a first format object storage, executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster, the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to the target data in the first format object storage.
Mudigonda teaches the source data and the target data being data from a data lake that is stored in a first format object storage (see Fig. 1, Fig. 5, para [0024-0025], para [0051], discloses source and target data from a data lake stored in cloud environment (first format object storage)); executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster (see Fig. 5, para [0035], para [0063], discloses schema partitioner for retrieving and identifying database columns and keywords in nodes (computing cluster) in cloud environment to be transformed to target data), the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to the target data in the first format object storage (see Figs. 4-5, para [0036-0037], para [0063], discloses applying technical and business rules in transforming source data that indicates which database columns to transform and generating a target schema for target database in the cloud environment).
Ash/Mudigonda are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash to utilize a computing cluster from disclosure of Mudigonda. The motivation to combine these arts is disclosed by Mudigonda as “improve the technology or technical field involving extract, transform, load (ETL) data processing pipelines” (para [0119]) and utilizing a computing cluster is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 8, Ash teaches a method comprising: receiving, via a graphical user interface, a definition of a transformation flow between source data and target data(see Figs. 1-2, Table 1, para [0044-0045], discloses Treasure Data platform receiving pipeline instruction between source and target data, it is known to one of ordinary skill in the art that Treasure Data features a browser based graphical user interface): generating a virtual procedure corresponding to the definition of the transformation flow (see Figs. 1-2, para [0044], discloses generating data pipeline instructions according to programmed pipeline of steps); storing the virtual procedure in an in-memory cloud database (see Figs. 1-2, para [0039], para [0044], discloses storing data pipeline instructions in target database system).
Ash does not explicitly teach the source data and the target data being data from a data lake that is stored in an a first format object storage; executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster, the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to the target data in the first format object storage.
Mudigonda teaches the source data and the target data being data from a data lake that is stored in a first format object storage (see Fig. 1, Fig. 5, para [0024-0025], para [0051], discloses source and target data from a data lake stored in cloud environment (first format object storage)); executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster (see Fig. 5, para [0035], para [0063], discloses schema partitioner for retrieving and identifying database columns and keywords in nodes (computing cluster) in cloud environment to be transformed to target data), the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to the target data in the first format object storage (see Figs. 4-5, para [0036-0037], para [0063], discloses applying technical and business rules in transforming source data that indicates which database columns to transform and generating a target schema for target database in the cloud environment).
Ash/Mudigonda are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash to utilize a computing cluster from disclosure of Mudigonda. The motivation to combine these arts is disclosed by Mudigonda as “improve the technology or technical field involving extract, transform, load (ETL) data processing pipelines” (para [0119]) and utilizing a computing cluster is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 15, Ash teaches a non-transitory machine-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors (see Fig. 4, para [0068], medium and processor) discloses to perform operations comprising: receiving, via a graphical user interface, a definition of a transformation flow between source data and target data (see Figs. 1-2, Table 1, para [0044-0045], discloses Treasure Data platform receiving pipeline instruction between source and target data, it is known to one of ordinary skill in the art that Treasure Data features a browser based graphical user interface): generating a virtual procedure corresponding to the definition of the transformation flow (see Figs. 1-2, para [0044], discloses generating data pipeline instructions according to programmed pipeline of steps); storing the virtual procedure in an in-memory cloud database (see Figs. 1-2, para [0039], para [0044], discloses storing data pipeline instructions in target database system).
Ash does not explicitly teach the source data and the target data being data from a data lake that is stored in a first format object storage; executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster, the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to target data in the first format object storage.
Mudigonda teaches the source data and the target data being data from a data lake that is stored in a first format object storage (see Fig. 1, Fig. 5, para [0024-0025], para [0051], discloses source and target data from a data lake stored in cloud environment (first format object storage)); executing the virtual procedure, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster (see Fig. 5, para [0035], para [0063], discloses schema partitioner for retrieving and identifying database columns and keywords in nodes (computing cluster) in cloud environment to be transformed to target data), the transformation job reading the source data from the first format object storage, applying one or more transformations specified in the definition of the transformation flow, and writing results to the target data in the first format object storage (see Figs. 4-5, para [0036-0037], para [0063], discloses applying technical and business rules in transforming source data that indicates which database columns to transform and generating a target schema for target database in the cloud environment).
Ash/Mudigonda are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash to utilize a computing cluster from disclosure of Mudigonda. The motivation to combine these arts is disclosed by Mudigonda as “improve the technology or technical field involving extract, transform, load (ETL) data processing pipelines” (para [0119]) and utilizing a computing cluster is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 2, 9, and 16 Ash/Mudigonda teaches a system of claim 1, a method of claim 8, and medium of claim 15.
Ash further teaches wherein the virtual procedure further comprises Python code for performing non-Structured Query Language (SQL)-based transformations the Python code being executed using a distributed computing framework (see Fig. 1, para [0021], para [0040], discloses Python code performing SQL transformations in a distributed computer system).
Regarding claims 3, 10, and 17 Ash/Mudigonda teaches a system of claim 1, a method of claim 8, and medium of claim 15.
Ash further teaches wherein the first format object storage is an open data format object storage, and wherein the transformation flow comprises one or more operations include filtering, aggregating, merging, or projecting data in the source data (see Fig. 2, Table 1, para [0051], discloses serial data transformations including filtering).
Claims 4, 6-7, 11, 13-14, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ash (US 2023/0385300) (hereinafter Ash) in view of Mudigonda et al. (US 2023/0074414) (hereinafter Mudigonda) as applied to claims 1, 8, and 15, and in further view of Syed et al. (US 2009/0276449)(hereinafter Syed).
Regarding claims 4, 11, and 18 Ash/Mudigonda teaches a system of claim 1, a method of claim 8, and medium of claim 15.
Ash/Mudigonda does not explicitly teach wherein the source data is a delta table.
Syed teaches wherein the source data is a delta table (see Fig. 1, para [0041], discloses source table is a delta table).
Ash/Mudigonda/Syed are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash/Mudigonda to utilize a source table as delta table from disclosure of Syed. The motivation to combine these arts is disclosed by Syed as “overhead data is saved in the logs used by the CDC component and still one can build an efficient delta load” (para [0148]) and utilizing a source table as delta table is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 6, 13, and 20 Ash/Mudigonda teaches a system of claim 1, a method of claim 8, and medium of claim 15.
Ash/Mudigonda does not explicitly wherein the graphical user interface provides a drag- and-drop interface for defining the transformation flow, including specifying the source data, target data, and transformation operations.
Syed teaches wherein the graphical user interface provides a drag- and-drop interface for defining the transformation flow, including specifying the source data, target data, and transformation operations (see Fig. 3, para [0021, 0027], discloses Extract, Load, and Transform task using GUI with drag and drop icons specifying a delta load task).
Ash/Mudigonda/Syed are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash/Mudigonda to utilize a drag and drop interface from disclosure of Syed. The motivation to combine these arts is disclosed by Syed as “overhead data is saved in the logs used by the CDC component and still one can build an efficient delta load” (para [0148]) and utilizing a drag and drop interface is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 7 and 14 Ash/Mudigonda teaches a system of claim 1 and a method of claim 8.
Ash/Mudigonda does not explicitly teach wherein the system further comprises a monitoring framework configured to track execution metrics of the transformation flow, including a number of records processed and execution time.
Syed teaches wherein the system further comprises a monitoring framework configured to track execution metrics of the transformation flow, including a number of records processed and execution time (see Fig. 6, para [0016], para [0051], discloses tables are read for a time-range covered by the delta load).
Ash/Mudigonda/Syed are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash/Mudigonda to utilize a drag and drop interface from disclosure of Syed. The motivation to combine these arts is disclosed by Syed as “overhead data is saved in the logs used by the CDC component and still one can build an efficient delta load” (para [0148]) and utilizing a drag and drop interface is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ash (US 2023/0385300) (hereinafter Ash) in view of Mudigonda et al. (US 2023/0074414) (hereinafter Mudigonda) as applied to claims 1, 8, and 15, and in further view of Yu et al. (US 2024/0386295)(hereinafter YU).
Regarding claims 5, 12, and 19 Ash/Mudigonda teaches a system of claim 1, a method of claim 8, and medium of claim 15.
Ash/Mudigonda does not explicitly teach wherein the target data is a delta table.
Yu teaches wherein the target data is a delta table (see Fig. 1, Fig. 3A, para [0041], discloses target table is a delta table).
Ash/Mudigonda/Yu are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Ash/Mudigonda to utilize a target table as a delta table from disclosure of Yu. The motivation to combine these arts is disclosed by Yu as “reduce inefficiencies within the executed elements of code, and improve or optimize a speed at which the distributed computing components of computing system 130 execute featurizer pipeline script” (para [0144]) and utilizing utilize a target table as a delta table is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Anilkumar et al. US Publication No. 2025/0245217.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to COURTNEY HARMON whose telephone number is (571)270-5861. The examiner can normally be reached M-F 9am - 5pm.
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/Courtney Harmon/Primary Examiner, Art Unit 2159
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